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339 lines
12 KiB
339 lines
12 KiB
#pragma once
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#include <atomic>
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#include <vector>
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#include <thread>
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#include <unordered_map>
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#include <shared_mutex>
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#include <semaphore.h>
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#include <sched.h>
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#include <numa.h>
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#include <dml/dml.hpp>
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namespace offcache {
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// execution policy selects in which way the data is supposed to be cached
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// and returned with the following behaviour is guaranteed in addition to the
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// returned value being valid:
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// Immediate: return as fast as possible
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// may return cached data, can return data in RAM
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// will trigger caching of the data provided
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// ImmediateNoCache: return as fast as possible and never trigger caching
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// same as Immediate but will not trigger caching
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// Relaxed: no rapid return needed, take time
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// will trigger caching and may only return
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// once the caching is successful but can still
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// provide data in RAM
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enum class ExecutionPolicy {
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Relaxed, Immediate, ImmediateNoCache
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};
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// the cache task structure will be used to submit and
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// control a cache element, while providing source pointer
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// and size in bytes for submission
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//
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// then the submitting thread may wait on the atomic "result"
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// which will be notified by the cache worker upon processing
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// after which the atomic-bool-ptr active will also become valid
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struct CacheTask {
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uint8_t* data_;
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size_t size_;
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uint8_t* result_ = nullptr;
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uint8_t* maybe_result_ = nullptr;
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std::atomic<bool> active_ { true };
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std::atomic<bool> valid_ { false };
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std::vector<dml::handler<dml::mem_copy_operation, std::allocator<uint8_t>>> handlers_;
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};
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// singleton which holds the cache workers
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// and is the place where work will be submited
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class CacheCoordinator {
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public:
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// cache policy is defined as a type here to allow flexible usage of the cacher
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// given a numa destination node (where the data will be needed), the numa source
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// node (current location of the data) and the data size, this function should
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// return optimal cache placement
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// dst node and returned value can differ if the system, for example, has HBM
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// attached accessible directly to node n under a different node id m
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typedef int (CachePolicy)(const int numa_dst_node, const int numa_src_node, const size_t data_size);
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// copy policy specifies the copy-executing nodes for a given task
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// which allows flexibility in assignment for optimizing raw throughput
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// or choosing a conservative usage policy
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typedef std::vector<int> (CopyPolicy)(const int numa_dst_node, const int numa_src_node);
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private:
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std::shared_mutex cache_mutex_;
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std::unordered_map<uint8_t*, CacheTask*> cache_state_;
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CachePolicy* cache_policy_function_ = nullptr;
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CopyPolicy* copy_policy_function_ = nullptr;
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dml::handler<dml::mem_copy_operation, std::allocator<uint8_t>> ExecuteCopy(const uint8_t* src, uint8_t* dst, const size_t size, const int node) const;
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void SubmitTask(CacheTask* task);
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CacheTask* CreateTask(const uint8_t *data, const size_t size) const;
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void DestroyTask(CacheTask* task) const;
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public:
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void Init(CachePolicy* cache_policy_function, CopyPolicy* copy_policy_function);
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// function to perform data access through the cache
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// behaviour depends on the chosen execution policy
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// Immediate and ImmediateNoCache return a cache task
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// with guaranteed-valid result value where Relaxed
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// policy does not come with this guarantee.
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CacheTask* Access(uint8_t* data, const size_t size, const ExecutionPolicy policy);
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// waits upon completion of caching
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static void WaitOnCompletion(CacheTask* task);
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// invalidates the given pointer
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// afterwards the reference to the
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// cache task object may be forgotten
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static void SignalDataUnused(CacheTask* task);
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// returns the location of the cached data
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// which may or may not be valid
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static uint8_t* GetDataLocation(CacheTask* task);
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void Flush();
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};
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}
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inline void offcache::CacheCoordinator::Init(CachePolicy* cache_policy_function, CopyPolicy* copy_policy_function) {
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cache_policy_function_ = cache_policy_function;
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copy_policy_function_ = copy_policy_function;
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// initialize numa library
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numa_available();
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}
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inline offcache::CacheTask* offcache::CacheCoordinator::Access(uint8_t* data, const size_t size, const ExecutionPolicy policy) {
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// the best situation is if this data is already cached
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// which we check in an unnamed block in which the cache
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// is locked for reading to prevent another thread
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// from marking the element we may find as unused and
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// clearing it
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{
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std::shared_lock<std::shared_mutex> lock(cache_mutex_);
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const auto search = cache_state_.find(data);
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if (search != cache_state_.end()) {
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if (search->second->size_ == size) {
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search->second->active_.store(true);
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// TODO: check for completed status depending on execution policy
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return search->second;
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}
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else {
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DestroyTask(search->second);
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cache_state_.erase(search);
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}
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}
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}
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// at this point the requested data is not present in cache
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// and we create a caching task for it
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CacheTask* task = CreateTask(data, size);
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if (policy == ExecutionPolicy::Immediate) {
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// in intermediate mode the returned task
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// object is guaranteed to be valid and therefore
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// its resulting location must be validated
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// after which we submit the task
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// maybe_result is then set by submit
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task->result_ = data;
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SubmitTask(task);
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return task;
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}
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else if (policy == ExecutionPolicy::ImmediateNoCache) {
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// for immediatenocache we just validate
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// the generated task and return it
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// we must also set maybe_result in case
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// someone waits on this
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task->result_ = data;
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task->maybe_result_ = data;
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return task;
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}
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else if (policy == ExecutionPolicy::Relaxed) {
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// for relaxed no valid task must be returned
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// and therefore we just submit and then give
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// the possible invalid task back with only
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// maybe_result set by submission
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SubmitTask(task);
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return task;
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}
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else {
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// this should not be reached
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}
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}
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inline void offcache::CacheCoordinator::SubmitTask(CacheTask* task) {
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// obtain numa node of current thread to determine where the data is needed
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const int current_cpu = sched_getcpu();
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const int current_node = numa_node_of_cpu(current_cpu);
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// obtain node that the given data pointer is allocated on
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int data_node = -1;
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get_mempolicy(&data_node, NULL, 0, (void*)task->data_, MPOL_F_NODE | MPOL_F_ADDR);
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// querry cache policy function for the destination numa node
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const uint32_t dst_node = cache_policy_function_(current_node, data_node, task->size_);
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// allocate data on this node and flush the unused parts of the
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// cache if the operation fails and retry once
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// TODO: smarter flush strategy could keep some stuff cached
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uint8_t* dst = numa_alloc_onnode(task->size_, dst_node);
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if (dst == nullptr) {
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Flush();
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dst = numa_alloc_onnode(task->size_, dst_node);
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if (dst == nullptr) {
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return;
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}
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}
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task->maybe_result_ = dst;
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// querry copy policy function for the nodes to use for the copy
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const std::vector<int> executing_nodes = copy_policy_function_(dst_node, data_node);
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const size_t task_count = executing_nodes.size();
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// at this point the task may be added to the cache structure
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// due to the task being initialized with the valid flag set to false
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{
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std::unique_lock<std::shared_mutex> lock(cache_mutex_);
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const auto state = cache_state_.insert({task->data_, task});
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// if state.second is false then no insertion took place
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// which means that concurrently whith this thread
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// some other thread must have accessed the same
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// resource in which case we must perform an abort
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// TODO: abort is not the only way to handle this situation
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if (!state.second) {
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// abort by doing the following steps
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// (1) free the allocated memory, (2) remove the "maybe result" as
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// we will not run the caching operation, (3) clear the sub tasks
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// for the very same reason, (4) set the result to the RAM-location
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numa_free(dst, task->size_);
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task->maybe_result_ = nullptr;
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task->result_ = task->data_;
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return;
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}
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}
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// each task will copy one fair part of the total size
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// and in case the total size is not a factor of the
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// given task count the last node must copy the remainder
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const size_t size = task->size_ / task_count;
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const size_t last_size = size + task->size_ % task_count;
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// save the current numa node mask to restore later
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// as executing the copy task will place this thread
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// on a different node
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const int nodemask = numa_get_run_node_mask();
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for (uint32_t i = 0; i < task_count; i++) {
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const size_t local_size = i + 1 == task_count ? size : last_size;
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const size_t local_offset = i * size;
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const uint8_t* local_src = task->data_ + local_offset;
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uint8_t* local_dst = dst + local_offset;
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const auto handler = ExecuteCopy(local_src, local_dst, local_size, executing_nodes[i]);
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task->handlers_.emplace_back(handler);
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}
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// set the valid flag of the task as all handlers
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// required for completion signal are registered
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task->valid_.store(true);
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task->valid_.notify_all();
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// restore the previous nodemask
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numa_run_on_node_mask(nodemask);
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}
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inline dml::handler<dml::mem_copy_operation, std::allocator<uint8_t>> offcache::CacheCoordinator::ExecuteCopy(const uint8_t* src, uint8_t* dst, const size_t size, const int node) {
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dml::data_view srcv = dml::make_view(reinterpret_cast<uint8_t*>(src), size);
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dml::data_view dstv = dml::make_view(reinterpret_cast<uint8_t*>(dst), size);
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numa_run_on_node(node);
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return dml::submit<path>(dml::mem_copy.block_on_fault(), srcv, dstv);
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}
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inline offcache::CacheTask* offcache::CacheCoordinator::CreateTask(const uint8_t* data, const size_t size) const {
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CacheTask* task = new CacheTask();
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task->data_ = data;
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task->size_ = size;
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return task;
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}
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inline void offcache::CacheCoordinator::DestroyTask(CacheTask* task) const {
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numa_free(task->result_, task->size_);
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delete task;
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}
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inline void offcache::CacheCoordinator::WaitOnCompletion(CacheTask* task) {
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task->valid_.wait(false);
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for (auto& handler : task->handlers_) {
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auto result = handler.get();
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// TODO: handle the returned status code
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}
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task->handlers_.clear();
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}
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inline uint8_t* offcache::CacheCoordinator::GetDataLocation(CacheTask* task) {
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return task->result_;
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}
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inline void offcache::CacheCoordinator::SignalDataUnused(CacheTask* task) {
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task->active_.store(false);
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}
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inline void offcache::CacheCoordinator::Flush() {
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// TODO: there probably is a better way to implement this flush
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{
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std::unique_lock<std::shared_mutex> lock(cache_mutex_);
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auto it = cache_state_.begin();
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while (it != cache_state_.end()) {
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if (it->second->active_.load() == false) {
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DestroyTask(it->second);
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cache_state_.erase(it);
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it = cache_state_.begin();
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}
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else {
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it++;
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}
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}
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}
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}
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